遙測影像為軍事情報的重要來源，在軍事影像判讀上有很大價值，本研究運用 WorldView-2 影像及LMS-Q680i 光達（Light Detection And Ranging，LiDAR）資料，針 對人造物進行影像分類萃取及邊緣分析；LiDAR 點雲資料結合全球定位系統(Global Positioning System，GPS)具有地面點位之(X、Y、Z)三維座標，產製出數值高程模型(Digital Elevation Model，DEM))和數值地表模型(Digital Surface Model，DSM)資料具有精細的 高程資訊，遙測影像進行分類萃取及邊緣分析成果加入輔助元素DEM 及DSM 資料， 以提升分類及邊緣分析精度，冀以準確萃取出人造物之資訊。

Remote Sensing Imagery, as an important source of military intelligence, has a great value on the military image distinguishing. This study is using World-View2 Remote sensing imagery, and LMS-Q680i Light Detection And Ranging(LiDAR) data to conduct artifact image classification and edge analysis. LiDAR point cloud data combined with Global Positioning System(GPS) has three-dimensional coordinates of the ground point (X、Y、Z) which can produce a Digital Elevation Model (DEM) and Digital Surface Model (DSM) with a fine elevation information. Remote Sensing Imagery Classification and Edge Analysis of the outcome of adding the auxiliary elements DEM and DSM data, can enhance the accuracy of classification and edge analysis, to conclude the precise artifact information.